Archivio Istituzionale della RicercaInitial efforts to report artificial intelligence (AI) incidents aimed to improve transparency, yet systematic studies have been rare. We analyzed all 639 real-world incidents in the emerging AI Incidents Database, devising an ethical framework focused on evaluating incidents along the dimensions of what, where, who, and how.
Decoding Real-World Artificial Intelligence Incidents / De Miguel Velázquez, Julia; Šćepanović, Sanja; Gvirtz, Andrés; Quercia, Daniele. - In: COMPUTER. - ISSN 0018-9162. - 57:11(2024), pp. 71-81. [10.1109/mc.2024.3432492]
Decoding Real-World Artificial Intelligence Incidents
Quercia, Daniele
2024
Abstract
Initial efforts to report artificial intelligence (AI) incidents aimed to improve transparency, yet systematic studies have been rare. We analyzed all 639 real-world incidents in the emerging AI Incidents Database, devising an ethical framework focused on evaluating incidents along the dimensions of what, where, who, and how.
File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
decoding24_ieee.pdf
accesso riservato
Tipologia:
1. Preprint / submitted version [pre- review]
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
891.54 kB
Formato
Adobe PDF
|
891.54 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
|
Decoding_Real-World_Artificial_Intelligence_Incidents.pdf
accesso riservato
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
927.7 kB
Formato
Adobe PDF
|
927.7 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/11583/2996104